PhD in NeuroAI and Computational Neuroscience
Core
Research at the intersection of neurobiologically inspired machine learning and computational neuroscience, focusing on efficient deep learning and continual reinforcement learning.
Role type
PhD researcher in NeuroAI and Computational Neuroscience
Builds
Research models and algorithms connecting biological neural circuits to AI architectures
Domain
Artificial Intelligence / Computational Neuroscience
Deliverable
research
Required skills
programming, mathematical modeling, deep learning, reinforcement learning, neural computation
Preferred skills
experience with spiking neural networks, event-based learning, Drosophila modeling
Technologies
deep neural networks, spiking neural networks, reinforcement learning frameworks
Responsibilities
Investigate computational roles of balanced excitatory/inhibitory circuits in deep learning; Explore continual learning in changing environments; Relate models to experimental findings in model organisms
Seniority
PhD student, research execution